Traditionally, baseband processing in a Global Positioning System (GPS) receiver is accomplished with special purpose digital hardware operating on digitized samples at a rate of 4 to 40 MHz. The higher performing receivers use the higher sampling rates. Currently, software implementations of GPS receivers have merely attempted to emulate this hardware processing. As such, these software implementations have been relegated to low performing, low sampling rate implementations.
Low performance is directly related to the low sampling rate. Prior to sampling, the digital baseband signal is filtered by a low-pass filter in order to prevent aliasing, where the bandwidth of the low-pass filter, which is referred to as the pre-sampling bandwidth, is limited by Nyquist criteria. More specifically, the pre-sampling bandwidth must be selected such that frequencies greater than ½ of the decimated sampling rate are removed from the digital baseband signal in order to prevent aliasing. However, in the case of low sampling rates, the low pre-sampling bandwidth obscures code transitions, which in a GPS system are transitions in the Pseudo-Random Noise (PRN) code in the L1 signal. Slower code transitions are more easily contaminated by reflected or multipath signals. Furthermore, optimum code error decriminators have been shown to produce higher Signal-to-Noise Ratio (SNR) results when the code transition is as fast as possible. As such, it has become standard for the sampling rate and the pre-sampling bandwidth to be direct measures of the potential performance of a GPS receiver.
One solution that provides improved performance is to increase the decimated sampling rate and thus the pre-sampling bandwidth. However, an increased sampling rate increases the required throughput of the processor of the GPS receiver. Thus, there remains a need for a decimator that provides a low sampling rate and does not require a low pre-sampling bandwidth.